User: Maryam

gravatar for Maryam
Maryam40
Reputation:
40
Status:
New User
Location:
Last seen:
6 months, 1 week ago
Joined:
9 months, 1 week ago
Email:
m**********@gmail.com

Posts by Maryam

<prev • 10 results • page 1 of 1 • next >
0
votes
1
answer
852
views
1
answers
Comment: C: FPKM quantile normalization
... Do you mean for example log transformation? ...
written 7 months ago by Maryam40
0
votes
1
answer
852
views
1
answers
Comment: C: FPKM quantile normalization
... Yes, when I did not receive any reply from you, because I was in a hurry to do my project, I asked my question in Bioconductor support. Ok, I will link both question to each other. Thanks. ...
written 7 months ago by Maryam40
0
votes
1
answer
852
views
1
answers
Comment: C: FPKM quantile normalization
... Many thanks Kevin. I downloaded the genecode version 19 gtf file and put it in my document. I am so thankful for your valuable advice to use Deseq2 normalization with gene adjustment. ...
written 7 months ago by Maryam40
0
votes
1
answer
852
views
1
answers
Comment: C: FPKM quantile normalization
... I finally found the way to do this. Here is the R code for whoever needs it. cts <- as.matrix(read.csv("Count_data.txt", row.names = 1, header= TRUE, sep="\t")) coldata <- read.csv("coldata.txt", row.names = 1, sep="\t") dds <- DESeqDataSetFromMatrix(countData = cts, colData = ...
written 7 months ago by Maryam40
0
votes
1
answer
852
views
1
answers
Comment: C: FPKM quantile normalization
... Many thanks Kevin, I have a look at [tximport][1], but I confused. How can i do that? I have gene-level counts, not transcripts level. [1]: http://bioconductor.org/packages/release/bioc/vignettes/tximport/inst/doc/tximport.html ...
written 7 months ago by Maryam40
0
votes
1
answer
852
views
1
answers
Comment: C: FPKM quantile normalization
... For example see this paper : https://www.pnas.org/content/115/50/E11874.short At the supplementary data, FPKM quantile normalization has been explained. ...
written 7 months ago by Maryam40
0
votes
1
answer
852
views
1
answers
Comment: C: FPKM quantile normalization
... Deseq normalization is a very good normalization methods in several studies but in metabolic modeling and integration of gene expression to metabolic network is not useful. Because it does not Normalize gene length. ...
written 7 months ago by Maryam40
13
votes
1
answer
852
views
7 follow
1
answer
FPKM quantile normalization
... Hi all, I have 250 samples from healthy and disease states. I want to integrate gene expression data into metabolic model and do flux balance analysis. Can I use FPKM directly for this work or should I normalize FPKM? For example in some publications I see that some researchers used quantile normali ...
flux balance analysis normalization rna-seq written 7 months ago by Maryam40
0
votes
1
answer
324
views
1
answers
Comment: C: Which normalization is good for gene expression classification and clustering
... so many thanks for your reply ...
written 9 months ago by Maryam40
3
votes
1
answer
324
views
1
answer
Which normalization is good for gene expression classification and clustering
... Hi All, I have gene expression (raw count and FPKM) from healthy and disease states. I'm going to do supervised and unsupervised classification on gene expression. As dimension reduction I'm going to get differential expression genes from DESeq2 and use these genes as features in my classification. ...
classification fpkm deseq2 normalization written 9 months ago by Maryam40

Latest awards to Maryam

No awards yet. Soon to come :-)

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1533 users visited in the last hour